CN109034935A - Products Show method, apparatus, computer equipment and storage medium - Google Patents
Products Show method, apparatus, computer equipment and storage medium Download PDFInfo
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- CN109034935A CN109034935A CN201810573702.7A CN201810573702A CN109034935A CN 109034935 A CN109034935 A CN 109034935A CN 201810573702 A CN201810573702 A CN 201810573702A CN 109034935 A CN109034935 A CN 109034935A
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
Abstract
The invention discloses a kind of Products Show method, apparatus, computer equipment and storage medium, which includes: to obtain the landing request information of user, and the landing request information includes user identifier；User's history behavioral data is obtained according to user identifier；According to the user's history behavioral data, target product recommendation information is generated and sent；It obtains user and selects information, it includes target product mark and behavioural information that the user, which selects information,；If the target product mark belongs to shared platform product, shared Products Show information is generated according to target product mark and the behavioural information.This method can improve the browse efficiency of user, improve the convenience of user's selection.
Description
Technical field
The present invention relates to computer fields more particularly to a kind of Products Show method, apparatus, computer equipment and storage to be situated between
Matter.
Background technique
Currently, not finding suitable product when user is in online shopping goods, it is desirable to which in different majors, company is chosen
When product, need to enter different specialized companies picking up product again, then carry out purchase operation.If user is not in the profession
Company carried out registration operation, it is also necessary to the operation re-registered.Such that the operation of user becomes cumbersome, and
And user cannot see that the similar product of other specialized companies in specialized company's shopping goods, so that user must be
Different specialized company's shopping goods, so that the operation of user becomes cumbersome.
Summary of the invention
Based on this, it is necessary in view of the above technical problems, provide a kind of efficiency that user can be improved in shopping goods
Products Show method, apparatus, computer equipment and storage medium.
A kind of Products Show method, comprising:
The landing request information of user is obtained, the landing request information includes user identifier；
User's history behavioral data is obtained according to the user identifier；
According to the user's history behavioral data, target product recommendation information is generated and sent；
It obtains user and selects information, it includes target product mark and behavioural information that the user, which selects information,；
If the target product mark belongs to shared platform product, believed according to target product mark and the behavior
Breath generates shared Products Show information.
A kind of Products Show device, comprising: login module, for obtaining the landing request information of user, the login is asked
Seeking information includes user identifier；
First obtains module, for obtaining user's history behavioral data according to the user identifier；
Target product sending module, for generating and sending target product recommendation according to the user's history behavioral data
Information；
Second obtains module, selects information for obtaining user, the user select information include target product mark and
Behavioural information；
Shared product sending module, if belonging to shared platform product for target product mark, according to the mesh
It marks product identification and the behavioural information generates shared Products Show information.
A kind of computer equipment, including memory, processor and storage are in the memory and can be in the processing
The computer program run on device, the processor realize the step of the said goods recommended method when executing the computer program
Suddenly.
A kind of computer readable storage medium, the computer-readable recording medium storage have computer program, the meter
The step of calculation machine program realizes the said goods recommended method when being executed by processor.
In the said goods recommended method, device, computer equipment and storage medium, generated by user's history behavioral data
Target product recommendation information, since the target product recommendation information is the possible interested product information of user, Neng Gouzeng
Add user carrying out selection when browsing to product, improves the browse efficiency of user, offer convenience for user.Further
Ground, by building shared platform, and by the Products Show of shared platform to user, user is when carrying out shopping goods, Neng Goucong
The product in more Products Co., Ltd is seen by one Products Co., Ltd, and makes and targetedly recommending, and reducing user will also enter
The troublesome operation of other Products Co., Ltd further improves the convenience of user's selection.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below by institute in the description to the embodiment of the present invention
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the invention
Example, for those of ordinary skill in the art, without any creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 is an application environment schematic diagram of Products Show method in one embodiment of the invention；
Fig. 2 is a flow chart of Products Show method in one embodiment of the invention；
Fig. 3 is the implementation flow chart of step S10 in Products Show method in one embodiment of the invention；
Fig. 4 is the implementation flow chart of step S12 in Products Show method in one embodiment of the invention；
Fig. 5 is the implementation flow chart of step S14 in Products Show method in one embodiment of the invention；
Fig. 6 is the implementation flow chart of step S50 in Products Show method in one embodiment of the invention；
Fig. 7 is a functional block diagram of Products Show device in one embodiment of the invention；
Fig. 8 is a schematic diagram of computer equipment in one embodiment of the invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are some of the embodiments of the present invention, instead of all the embodiments.According to this hair
Embodiment in bright, every other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, shall fall within the protection scope of the present invention.
Products Show method provided by the present application, can be applicable in the application environment such as Fig. 1, wherein client (computer
Equipment) it is communicated by network with server-side.Client obtains the logging request of user, which is sent to service
End.Server-side generates target product recommendation information after getting the logging request, according to the user identifier, is sent to client
End.Server-side is obtained by calculating similarity and degree of association building shared platform between different product according to from client
The user arrived selects information, generates shared Products Show information, is sent to client.Wherein, client (computer equipment) can
With but be not limited to various personal computers, laptop, smart phone, tablet computer and portable wearable device.Service
End can be realized with the server cluster of the either multiple server compositions of independent server.
In one embodiment, as shown in Fig. 2, providing a kind of Products Show method, the service in Fig. 1 is applied in this way
It is illustrated, includes the following steps: for end
S10: obtaining the landing request information of user, and landing request information includes user identifier.
In embodiments of the present invention, landing request information refers to that client is stepped on getting input of the user in login interface
Information is recorded later by processing, and is sent to the information in server-side.Landing request information includes user identifier.The user identifier
After forming landing request information, which is sent to server-side by client, and server-side obtains the logging request
Information.
Optionally, landing request information be also possible to client get user input log-on message after add
It is close to obtain, by the way that the log-on message that user inputs is encrypted it can guarantee that landing request information is transmitted across in data
Safety in journey.
S20: user's history behavioral data is obtained according to user identifier.
In embodiments of the present invention, the user identifier gets what the user carried out according to user's history behavioral data
The data of operation behavior, operation behavior include browsing behavior and buying behavior of the user to the product in Products Co., Ltd.It needs
Illustrate, which is under corporate boss's account platform, and the one or more Products Co., Ltd for including, user can root
The product in the Products Co., Ltd is carried out clear according to the log-on message into a Products Co., Ltd under corporate boss's account platform
It lookes at and buys.
Optionally, server-side obtains user's history behavioral data in such a way that data are buried a little.
Specifically, in such a way that data are buried a little, the implementation method for obtaining user's history behavioral data be can be by adding
Enter to bury point code, for acquiring the data for needing the operation behavior of the user information and user that return to server-side.For example, browsing
The corresponding browsing linking button of behavior and the corresponding purchase linking button of buying behavior.I.e. user is carrying out browsing behavior to product
When with buying behavior, need to carry out the browsing linking button of the product and purchase linking button corresponding operation (such as: point
Hit) product is browsed and bought to realize, when the browsing linking button for detecting the product is clicked, then judgement should
User has carried out a browsing behavior to the product；When the purchase linking button for detecting the product is clicked, then judgement should
User has carried out buying behavior to the product.
Preferably, obtaining user's history behavioral data according to user identifier can be the user's history obtained in intended duration
Behavioral data.Specifically, such as the intended duration is three months, and user is within nearest five middle of the month, first trimester to a certain production
Products browse in product company 10 times, respectively first month has browsed 3 times, and second month has browsed 5 times, third month is clear
It has look at 2 times, in next two middle of the month, which does not browse the product of the Products Co., Ltd, then it is assumed that, the user
2 browsing behaviors have been carried out to the product in a certain Products Co., Ltd in intended duration.
S30: according to user's history behavioral data, target product recommendation information is generated and sent.
In embodiments of the present invention, target product recommendation information is the product information group by the portioned product in Products Co., Ltd
At recommendation information.
Specifically, it is gone according to the browsing behavior of the product to the Products Co., Ltd in the user's history behavioral data, collection
For, actively score behavior and buying behavior, obtain the interested product of the user, and the use is calculated using collaborative filtering
The possible interested product in family generates target product recommendation information according to the possible interested product of the user and feeds back to client
End, shows in the client, preferentially selects for user.
Further, interest level is carried out to the product according to user's history behavioral data of the user to a certain part product
It calculates, concrete mode, which can be, integrates the behavior for including in user's history behavioral data with reference to actively scoring or combining
Evaluation, obtains the interest level, if the interest level reaches preset threshold value, then it is assumed that the user is emerging to the product sense
Interest.
If identical interested product quantity is more between two users, then it is assumed that the two users may have identical
Interest.It therefore, can be according to the product for thering is the user of identical interest to browse with the user when user browses a product
Information generates target product recommendation information, and is sent to client.
S40: it obtains user and selects information, it includes target product mark and behavioural information that user, which selects information,.
In embodiments of the present invention, the production which selects information to be shown on the client for user according to Products Co., Ltd
Product select one of product to carry out corresponding operation behavior, and the product of user selection is target product, the operation behavior
It can be browsing behavior or buying behavior.Target product is identified as the unique identification of the target product of user selection.Behavior
Information is the particular content of the operation behavior, including browsing behavior, collection behavior and buying behavior.Client is according to the operation row
It makes a living into behavioural information, and identifies composition user with the target product of the target product and select information, client is by user later
Selection information is sent to server-side.
S50: it if target product mark belongs to shared platform product, is generated altogether according to target product mark and behavioural information
Enjoy Products Show information.
In embodiments of the present invention, shared platform product be each Products Co., Ltd by respective product according to certain share,
The product being put into shared platform, the product in the shared platform can be shown in the client of each Products Co., Ltd, for client
Browsing and purchase.
If the target product mark of the target product can be found in shared platform, determine that the target product identifies
Corresponding target product belongs to shared platform product.Further, it is generated according to target product mark and behavioural information shared
Products Show information, is sent to client.Wherein, which includes the phase of the target product in shared platform
Close information.
In the present embodiment, target product recommendation information is generated by user's history behavioral data, due to the target product
Recommendation information be user may interested product information therefore can increase user when browse to product
Selection, improves the browse efficiency of user, offers convenience for user.Further, by building shared platform, and by shared platform
Products Show to user, user can see in more Products Co., Ltd when carrying out shopping goods from a Products Co., Ltd
Product, and make and targetedly recommending, the troublesome operation of other Products Co., Ltd will be entered by reducing user also, be further increased
The convenience of user's selection.
In one embodiment.As shown in figure 3, the Products Show method further includes following steps before step S10:
S11: obtaining the product information of each interface, and product information includes primary products mark and product operation record.
Specifically, corresponding interface is set in the server of each Products Co., Ltd in corporate boss's account platform, is used for
The interaction of data is carried out, can be in communication with each other between each interface.The primary products are identified as the unique of product in each interface
Mark.The product operation is recorded as in past a cycle, for example, in one month, three months or half a year, different user
Collection record and product purchase are cancelled to the record that the product is operated, including products browse record, product collection record, product
Buy record etc..
S12: recording according to product operation, obtains the similarity between primary products mark.
In embodiments of the present invention, the similarity between different primary products mark is function between two products, produces
The similarity degree of product attribute or product category etc..It wherein, can if the similarity degree between two primary products marks is higher
To think to identify the interested user of corresponding product to one of primary products, another primary products can also be identified and be corresponded to
Product it is interested.Specifically, it can be recorded and be calculated by the product operation to user, obtained according to the calculated result every
Similarity between one primary products mark.
Further, the range of calculating include in shared platform each primary products identify it is similar between corresponding product
Spend ε.It when calculating the similarity ε between two primary products marks, is calculated, is obtained according to the content that product operation records
Each primary products identify the similarity ε between corresponding product in shared platform.The result calculated is in shared platform
Similarity ε between each product and other products.
For example, having product A, product B and products C in shared platform, then product A and product B, product A and production are calculated separately
Similarity between product C and product B and products C, obtained calculated result can be expressed as εAB, εACAnd εBC。
S13: identifying each primary products, which is identified M original before corresponding similarity comes
The corresponding product of product identification is as like product, wherein M is a positive integer.
Specifically, after the similarity ε that different primary products identify between corresponding product is calculated, according to shared flat
The primary products mark of each product in platform, by the phase of other primary products mark and primary products mark in shared platform
It is ranked up from big to small like degree, M before ranking primary products is identified what corresponding product was identified as the primary products
Like product.It should be noted that the particular number of M can be set according to the similarity being calculated, for example, it may be
Similarity threshold is set, the primary products that similarity is greater than or equal to similarity threshold are identified into corresponding product as similar production
Product.
S14: product operation record includes product purchased record, according to product purchased record, obtains primary products and identifies it
Between the degree of association.
In embodiments of the present invention, product purchased record is the number that each product is purchased.Different primary products marks
Degree of correlation of the degree of association between different product between corresponding product, for example, mobile phone, sticking film for mobile phone, mobile phone protecting case,
In the products such as mobile phone charging wire, earphone or mobile charger, although product function is different, the function of these products is phase
Mutual correlation, if sticking film for mobile phone is for protecting mobile phone screen or mobile phone shell, mobile phone protecting case is for protecting handset simultaneously
Play beauty function etc..User is while buying mobile phone, it is possible to can buy other products associated with mobile phone.
Specifically, the range of calculating includes the association that each primary products identify between corresponding product in shared platform
Degree.It in calculating correlation, is calculated, is obtained in shared platform between each product according to the content of product purchased record
The degree of association.The result calculated is the degree of association between product and other products in each shared platform.
S15: each primary products are identified, which is identified into the corresponding degree of association and comes the original of top N
The corresponding product of product identification is as related product, wherein N is a positive integer.
Specifically, after the degree of association that each primary products identify between corresponding product is calculated, according to shared flat
The primary products mark of each product in platform, by the pass of other primary products mark and primary products mark in shared platform
Connection degree is ranked up from big to small, and the primary products of ranking top N are identified what corresponding product was identified as the primary products
Related product.It should be noted that the particular number of N can be set according to the degree of association being calculated, for example, it may be
Degree of association threshold value is set, the primary products that the degree of association is greater than or equal to the degree of association threshold value are identified into corresponding product as association
Product.
In the present embodiment, by calculating similarity and the degree of association in shared platform between each product, and according to the phase
Classify like degree and the degree of association to product, can when user carries out operation behavior to product, according to the operation behavior,
More reasonably recommend the product in shared platform to user, improve the validity of Products Show degree, also improves the browsing of user
Efficiency.
In one embodiment, as shown in figure 4, recording according to product operation in step S12, each primary products are obtained
Similarity between mark, specifically comprises the following steps:
S121: it is recorded according to product operation and calculates user interest scores.
Specifically, products browse record, product collection record, the product for including for product operation record cancel collection record
Different weights is set with product purchased record.Wherein, due to can be assumed that the user to the product by cancelling collection behavior
It has been lost interest that, and user is interested in a product can just browse to the content of the product, if to the content of the product
It is interested, can further the product is collected, if the content to the product is extremely interested, it is possible to can to the product into
Row purchase.Therefore, the size relation of each weight can be with are as follows: product is cancelled collection record < 0 < products browse record < product collection and remembered
Record < product purchased record.Specific weight size can be set according to the actual situation, here with no restrictions.
After the weight for setting different product operation note, remembered according to product operation of the user for a certain product
Record, calculates user interest scores.
For example, setting product cancels collection record weight=- 2, products browse records weight=1, product collection record power
Value=3, product purchased record weight=5.User has carried out browsing behavior to a certain product, and is made that collection row to the product
For subsequent and be made that the product and cancel collection behavior, therefore the user is clear to user interest scores=product of the product
Record weight+product collection record weight+product of looking at cancels collection record weight=1+3+ (- 2)=2.
S122: according to user interest scores, user's quantity interested of each primary products mark is obtained.
Specifically, user interest scores can be screened by the way that a user interest threshold value is arranged.If user interest is commented
Point >=setting user interest threshold value, then judge that user is interested in the product, if user interest threshold is arranged in user interest scores <
Value, then judge that user loses interest in the product.The user that corresponding product calculates each user is identified to each primary products
It is whether interested in the product to judge each user for interest scores, and the interested quantity of the user for counting each product
N。
Such as: in the example of step S121, calculating a user is 2 to the user interest scores of the product, if user
Interest threshold is 3, then illustrates that the user loses interest in the product.
S123: the phase between each primary products mark is calculated according to user's quantity interested that each primary products identify
Like degree.
Specifically, the similarity that can be calculated by the following formula between two primary products marks:
Wherein, εijThe similarity between i and primary products mark j is identified for primary products, | N (i) | it is to primary products
The interested number of users of i is identified, | N (j) | it is that the interested number of users of j is identified to primary products, | N (i) ∩ N (j) | be
I is identified to primary products simultaneously and primary products identify the interested number of users of j.It should be noted that should be simultaneously to original
Product identification i and the primary products mark interested number of users of j can by count same user to primary products identify i and
The primary products mark all interested quantity of j obtains.
In the present embodiment, the similarity between different product is calculated to the interest level of product by counting user,
Similar product can be divided into one kind based on the similarity, be conducive to when user browses a certain product, it will be in this
The similar Products Show of product can save user in the time of shopping goods to user.
In one embodiment, as shown in figure 5, in step S14, according to product purchased record, primary products is obtained and identify it
Between the degree of association, specifically comprise the following steps:
S141: according to product purchased record, statistics in the given time bought by same user by two primary products marks
Purchase number.
In embodiments of the present invention, (primary products identify A and primary products to two primary products marks in the given time
B is identified, calls product A and product B in the following text) the purchase number bought by same user are as follows: in the given time (for example, one month, three
A month or half a year etc.), purchase product A buys the number of users of product B again.For example, for product A and product B, it is predetermined at this
In time, product A and product B are had purchased by 100 users, wherein have 40 users within the scheduled time, that is, buy
Product A, also has purchased product B, then product A and product B is bought by same user purchase number is 40.
Specifically, within the predetermined time, after same user buys a product, other products, explanation are had purchased
There may be relevances for two purchased products.If two products number purchased simultaneously is more, illustrate the two products
Between relevance it is higher.
S142: the degree of association between each primary products mark is obtained using TF-IDF algorithm.
It specifically, can (word frequency be against text probability index, term frequency-inverse using TF-IDF
Document frequency) algorithm calculates the degree of association between two primary products marks, for example, calculating product A and product B
Between the degree of association when, the degree of association that is calculated using the following equation between two primary products mark:
The degree of association=TF*IDF
Wherein, TF is word frequency (Term Frequency), and IDF is inverse document frequency (Inverse Document
Frequency), MAFor the number that product A in the given time is purchased, MBTime being purchased for product B in the given time
Number, MA∩MBFor the number that product A product B is bought by same user in the given time, M is number of deals total in the predetermined time
Mesh.
In the present embodiment, the purchase bought by same user is identified by counting two primary products in the given time
Number, and the degree of association between different primary products marks is calculated using TF-IDF algorithm, reasonably it can recommend to produce to user
Product enrich the purchase selection of user.
In one embodiment, it as shown in fig. 6, in step S50, i.e., is generated according to target product mark and behavioural information shared
Products Show information, specifically comprises the following steps:
S51: if behavioural information is browsing behavior, corresponding like product is obtained according to target product mark.
In embodiments of the present invention, which is user from one of interface, is showed to the client of the interface
The browse operation that carries out of product, wherein target product is identified as user and selects a certain product as target product from the interface,
And browse operation, the mark of the corresponding target product are carried out to the target product.
When detecting that user carries out browse operation to one of target product, then obtain and target product mark pair
The like product answered.Specifically, it obtains and the target product identifies identical primary products and identifies corresponding like product.
S52: corresponding like product is identified according to target product and generates shared Products Show information.
Specifically, according to the like product corresponding with target product mark got, shared Products Show is generated
Information feeds back to client, and user is while browsing target product mark corresponding product, additionally it is possible to see and the target
The similar product of the corresponding product of product identification.
S53: if behavioural information is buying behavior, corresponding related product is obtained according to target product mark.
In embodiments of the present invention, which is user from one of interface, is showed to the client of the interface
Product carry out purchase operation, wherein target product is identified as user and selects a certain product as target product from the interface, and
Purchase operation, the mark of the corresponding target product are carried out to the target product.
After detecting that user carries out purchase operation to one of target product, then obtains target product mark and correspond to
Related product.Specifically, it obtains and the target product identifies identical primary products and identifies corresponding related product.
S54: corresponding related product is identified according to target product and generates shared Products Show information.
Specifically, according to the related product corresponding with target product mark got, shared Products Show is generated
Information feeds back to client, and user is while buying target product mark corresponding product, additionally it is possible to see and the target
The associated product of the corresponding product of product identification.
In the present embodiment, the shared Products Show information generated according to the behavioural information of user, rather than directly will be with
The target product mark associated product of phase Sihe recommends user simultaneously, validity when can be improved as user's recommended products.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit
It is fixed.
In one embodiment, a kind of Products Show device is provided, which pushes away with product in above-described embodiment
Recommend method one-to-one correspondence.As shown in fig. 7, the Products Show device includes that login module 71, first obtains module 72, target product
Sending module 73, second obtains module 74 and shared product sending module 75.Detailed description are as follows for each functional module:
Login module 71, for obtaining the landing request information of user, landing request information includes user identifier；
First obtains module 72, for obtaining user's history behavioral data according to user identifier；
Target product sending module 73, for generating and sending target product recommendation according to user's history behavioral data
Breath；
Second obtains module 74, selects information for obtaining user, it includes target product mark and row that user, which selects information,
For information；
Shared product sending module 75, if belonging to shared platform product for target product mark, according to target product
Mark and behavioural information generate shared Products Show information.
Preferably, the Products Show device further include:
Interface message obtains module 711, and for obtaining the product information of each interface, product information includes primary products mark
Know and product operation records；
Similarity obtains module 712, for recording according to product operation, obtains the similarity between primary products mark；
Similarity arranges module 713, for identifying for each primary products, which is identified corresponding similar
Degree comes preceding M primary products and identifies corresponding product as like product, wherein M is a positive integer；
The degree of association obtains module 714, is used for, and according to product purchased record, obtains the degree of association between primary products mark,
Wherein product operation record includes product purchased record；
The degree of association arranges module 715, and for identifying for each primary products, which is identified corresponding association
The primary products that degree comes top N identify corresponding product as related product, wherein N is a positive integer.
Preferably, similarity acquisition module 712 includes:
Interest scores computational submodule 7121 calculates user interest scores for recording according to product operation；
Quantity statistics submodule 7122, for obtaining user's sense of each primary products mark according to user interest scores
Interest quantity.
Similarity calculation submodule 7123, user's quantity interested for being identified according to each primary products calculate each
Similarity between primary products mark.
Preferably, degree of association acquisition module 714 includes:
Buy number statistic submodule 7141, for according to product purchased record, statistics in the given time two it is original
The purchase number that product identification is bought by same user；
Calculation of relationship degree submodule 7142, for obtaining the association between each primary products mark using TF-IDF algorithm
Degree.
Preferably, which includes:
First judging submodule 751 identifies according to target product if being browsing behavior for behavioural information and obtains correspondence
Like product；
First recommends submodule 752, generates shared Products Show for identifying corresponding like product according to target product
Information；
Second judgment submodule 753 identifies according to target product if being buying behavior for behavioural information and obtains correspondence
Related product；
Second recommends submodule 754, generates shared Products Show for identifying corresponding related product according to target product
Information.
Specific about Products Show device limits the restriction that may refer to above for Products Show method, herein not
It repeats again.Modules in the said goods recommendation apparatus can be realized fully or partially through software, hardware and combinations thereof.On
Stating each module can be embedded in the form of hardware or independently of in the processor in computer equipment, can also store in a software form
In memory in computer equipment, the corresponding operation of the above modules is executed in order to which processor calls.
In one embodiment, a kind of computer equipment is provided, which can be server, internal junction
Composition can be as shown in Figure 8.The computer equipment include by system bus connect processor, memory, network interface and
Database.Wherein, the processor of the computer equipment is for providing calculating and control ability.The memory packet of the computer equipment
Include non-volatile memory medium, built-in storage.The non-volatile memory medium is stored with operating system, computer program and data
Library.The built-in storage provides environment for the operation of operating system and computer program in non-volatile memory medium.The calculating
The database of machine equipment is for storing product information and user data.The network interface of the computer equipment is used for and external end
End passes through network connection communication.To realize a kind of Products Show method when the computer program is executed by processor.
In one embodiment, a kind of computer equipment is provided, including memory, processor and storage are on a memory
And the computer program that can be run on a processor, processor perform the steps of when executing computer program
The landing request information of user is obtained, landing request information includes user identifier；
User's history behavioral data is obtained according to user identifier；
According to user's history behavioral data, target product recommendation information is generated and sent；
It obtains user and selects information, it includes target product mark and behavioural information that user, which selects information,；
If target product mark belongs to shared platform product, shared produce is generated according to target product mark and behavioural information
Product recommendation information.
In one embodiment, a kind of computer readable storage medium is provided, computer program is stored thereon with, is calculated
Machine program performs the steps of when being executed by processor
The landing request information of user is obtained, landing request information includes user identifier；
User's history behavioral data is obtained according to user identifier；
According to user's history behavioral data, target product recommendation information is generated and sent；
It obtains user and selects information, it includes target product mark and behavioural information that user, which selects information,；
If target product mark belongs to shared platform product, shared produce is generated according to target product mark and behavioural information
Product recommendation information.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, the computer program can be stored in a non-volatile computer
In read/write memory medium, the computer program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein,
To any reference of memory, storage, database or other media used in each embodiment provided herein,
Including non-volatile and/or volatile memory.Nonvolatile memory may include read-only memory (ROM), programming ROM
(PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM) or flash memory.Volatile memory may include
Random access memory (RAM) or external cache.By way of illustration and not limitation, RAM is available in many forms,
Such as static state RAM (SRAM), dynamic ram (DRAM), synchronous dram (SDRAM), double data rate sdram (DDRSDRAM), enhancing
Type SDRAM (ESDRAM), synchronization link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM
(RDRAM), direct memory bus dynamic ram (DRDRAM) and memory bus dynamic ram (RDRAM) etc..
It is apparent to those skilled in the art that for convenience of description and succinctly, only with above-mentioned each function
Can unit, module division progress for example, in practical application, can according to need and by above-mentioned function distribution by different
Functional unit, module are completed, i.e., the internal structure of described device is divided into different functional unit or module, more than completing
The all or part of function of description.
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations；Although referring to aforementioned reality
Applying example, invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each
Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features；And these are modified
Or replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution should all
It is included within protection scope of the present invention.
Claims (10)
1. a kind of Products Show method characterized by comprising
The landing request information of user is obtained, the landing request information includes user identifier；
User's history behavioral data is obtained according to the user identifier；
According to the user's history behavioral data, target product recommendation information is generated and sent；
It obtains user and selects information, it includes target product mark and behavioural information that the user, which selects information,；
If the target product mark belongs to shared platform product, raw according to target product mark and the behavioural information
At shared Products Show information.
2. Products Show method as described in claim 1, which is characterized in that in the landing request information for obtaining user
Before step, the Products Show method further include:
The product information of each interface is obtained, the product information includes primary products mark and product operation record；
It is recorded according to the product operation, obtains the similarity between the primary products mark；
Each primary products are identified, the primary products which identifies M before corresponding similarity comes are identified
Corresponding product is as like product, wherein M is a positive integer；
The product operation record obtains the primary products mark according to the product purchased record including product purchased record
The degree of association between knowledge；
Each primary products are identified, which is identified into the primary products mark that the corresponding degree of association comes top N
Corresponding product is as related product, wherein N is a positive integer.
3. Products Show method as claimed in claim 2, which is characterized in that it is described to be recorded according to the product operation, it obtains
Similarity between the primary products mark, comprising:
It is recorded according to the product operation and calculates user interest scores；
According to the user interest scores, user's quantity interested of each primary products mark is obtained；
It is calculated between each primary products mark according to the user quantity interested of each primary products mark
The similarity.
4. Products Show method as claimed in claim 2, which is characterized in that it is described according to the product purchased record, it obtains
The degree of association between the primary products mark, comprising:
According to the product purchased record, count what two primary products marks in the given time were bought by same user
Buy number；
The degree of association between each primary products mark is obtained using TF-IDF algorithm.
5. Products Show method as described in claim 1, which is characterized in that described according to target product mark and described
Behavioural information generates shared Products Show information, comprising:
If the behavioural information is browsing behavior, corresponding like product is obtained according to target product mark；
Corresponding like product, which is identified, according to the target product generates shared Products Show information；
If the behavioural information is buying behavior, corresponding related product is obtained according to target product mark；
Corresponding related product, which is identified, according to the target product generates shared Products Show information.
6. a kind of Products Show device characterized by comprising
Login module, for obtaining the landing request information of user, the landing request information includes user identifier；
First obtains module, for obtaining user's history behavioral data according to the user identifier；
Target product sending module, for generating and sending target product recommendation information according to the user's history behavioral data；
Second obtains module, selects information for obtaining user, it includes target product mark and behavior that the user, which selects information,
Information；
Shared product sending module produces if belonging to shared platform product for target product mark according to the target
Product mark and the behavioural information generate shared Products Show information.
7. Products Show device as claimed in claim 6, which is characterized in that described device further include:
Interface message obtains module, and for obtaining the product information of each interface, the product information includes primary products mark
It is recorded with product operation；
Similarity obtains module, for recording according to the product operation, obtains the similarity between the primary products mark；
Similarity arranges module, for identifying for each primary products, which is identified corresponding similarity and is come
Preceding M of primary products identify corresponding product as like product, wherein M is a positive integer；
The degree of association obtains module, includes product purchased record for product operation record, according to the product purchased record,
Obtain the degree of association between the primary products mark；
The degree of association arranges module, for identifying for each primary products, which is identified the corresponding degree of association and is come
The primary products of top N identify corresponding product as related product, wherein N is a positive integer.
8. Products Show device as claimed in claim 7, which is characterized in that the similarity obtains module and includes:
Interest scores computational submodule calculates user interest scores for recording according to the product operation；
Quantity statistics submodule, for obtaining user's sense of each primary products mark according to the user interest scores
Interest quantity；
Similarity calculation submodule, it is each for being calculated according to the user quantity interested of each primary products mark
The similarity between the primary products mark.
9. a kind of computer equipment, including memory, processor and storage are in the memory and can be in the processor
The computer program of upper operation, which is characterized in that the processor realized when executing the computer program as claim 1 to
The step of any one of 5 Products Show method.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In the step of realization Products Show method as described in any one of claim 1 to 5 when the computer program is executed by processor
Suddenly.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810573702.7A CN109034935B (en) | 2018-06-06 | 2018-06-06 | Product recommendation method, device, computer equipment and storage medium |
| PCT/CN2018/092361 WO2019232822A1 (en) | 2018-06-06 | 2018-06-22 | Product recommendation method and apparatus, computer device, and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810573702.7A CN109034935B (en) | 2018-06-06 | 2018-06-06 | Product recommendation method, device, computer equipment and storage medium |
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| CN109034935B CN109034935B (en) | 2023-04-21 |
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| WO (1) | WO2019232822A1 (en) |
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| Publication number | Publication date |
|---|---|
| WO2019232822A1 (en) | 2019-12-12 |
| CN109034935B (en) | 2023-04-21 |
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